Lidar system and method of operation

ABSTRACT

A LIDAR system, preferably including one or more: optical emitters, optical detectors, beam directors, and/or processing modules. A method of LIDAR system operation, preferably including: determining a signal, outputting the signal, receiving a return signal, and/or analyzing the return signal.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.16/663,142, filed 24 Oct. 2019, which claims the benefit of U.S.Provisional Application Ser. No. 62/749,795, filed on 24 Oct. 2018, andof U.S. Provisional Application Ser. No. 62/750,058, filed on 24 Oct.2018, each of which is incorporated in its entirety by this reference.

TECHNICAL FIELD

This invention relates generally to the object detection and/or imagingfield, and more specifically to a new and useful lidar system and methodof operation in the object detection and/or imaging field.

BACKGROUND

Typical lidar systems and methods of use have fixed range, resolution,and/or accuracy. Further, their performance with respect to thesemetrics is typically significantly limited due to a need to wait foreach light pulse to return before emitting the next light pulse. Thus,there is a need in the object detection field to create a new and usefullidar system and method of operation.

BRIEF DESCRIPTION OF THE FIGURES

FIGS. 1A-1B are flowchart representations of an embodiment of the methodand an example of the embodiment, respectively.

FIG. 2A is a schematic representation of an embodiment of the system.

FIG. 2B is a schematic representation of the embodiment of the system inuse.

FIGS. 3A-3B are schematic representations of examples of determiningsignals.

FIGS. 4A-4B are schematic representations of examples of analyzingreturn signals.

FIG. 5 is a schematic representation of a specific example of analyzinga return signal.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

The following description of the preferred embodiments of the inventionis not intended to limit the invention to these preferred embodiments,but rather to enable any person skilled in the art to make and use thisinvention.

1. Overview.

A method 100 of lidar system operation preferably includes: determininga signal S110; outputting the signal S120; receiving a return signalS130; and/or analyzing the return signal S140 (e.g., as shown in FIGS.1A-1B). However, the method 100 can additionally or alternativelyinclude any other suitable elements performed in any suitable manner.The method 100 is preferably performed using a lidar system 200, but canadditionally or alternatively be performed using any other suitablesystem(s).

2. System.

The lidar system 200 preferably includes one or more: optical emitters210; optical detectors 220; beam directors 230; and/or processingmodules 240 (e.g., as shown in FIG. 2A). However, the system 200 canadditionally or alternatively include any other suitable elements in anysuitable arrangement.

The optical emitter(s) 210 preferably function to (e.g., are operableto) emit one or more optical signals. The optical signals are preferablybeam-like (e.g., laser beams), but can additionally or alternativelyhave any other suitable optical characteristics.

The optical emitters preferably include one or more lasers (e.g., diodelasers). The lasers can include, for example, edge-emitting lasers,surface-emitting lasers (e.g., VCSELs), fiber coupled lasers, and/orlasers of any other suitable types. The lasers are preferably continuouswave lasers (e.g., operable and/or configured to emit substantiallycontinuous wave radiation) but can additionally or alternatively includepulsed lasers (e.g., operable and/or configured to emit pulses ofradiation) and/or any other suitable lasers. In one specific example,one or more of the lasers emit light with a wavelength of substantially900 nm (e.g., 890-910 nm, 875-925 nm, etc.). In a second specificexample, one or more of the lasers emit light with a wavelength ofsubstantially 1550 nm (e.g., 1540-1560 nm, 1525-1575 nm, etc.). In athird specific example, one or more of the lasers emit light with awavelength of substantially 835 nm (e.g., 820-850 nm, 800-870 nm, etc.).The light intensity emitted by the laser is preferably lower than orequal to the limit prescribed by regulatory standards (e.g., the lasercan be compliant with IEC-60825, IEC-62471, etc.), but can alternativelybe higher. The signal power can be within regulatory limits (e.g., lessthan a threshold power, such as 5 W 2 W, 1 W, 500 mW, 200 mW, 100 mW, 50mW, 20 mW, 10 mW, 5 mW, 2 mW, 1 mW, 0.5 mW, 0.2 mW, or 0.1 mW, etc.),preferably less than 1 mW, but can alternatively be higher or lower.However, the lasers can additionally or alternatively include any othersuitable lasers.

Each optical emitter 210 preferably includes one or more modulators.Each modulator is preferably operable to modulate one or more aspects(e.g., phase, intensity, wavelength, etc.) of the light emitted by theemitter. However, the system 200 can additionally or alternativelyinclude any other suitable optical emitters.

The optical detector(s) 220 preferably function to (e.g., are operableto) generate an electrical signal (e.g., current, voltage, etc.) inresponse to optical detection (e.g., representative of the detectedoptical signal), but can additionally or alternatively generate anyother suitable signal (e.g., representative of the detected opticalsignal) in response to optical signal detection. For example, theoptical detectors can include one or more photodiodes (e.g., avalanchephotodiodes). The optical detector(s) 220 can optionally include (and/orbe supplemented by) one or more demodulators (e.g., digitaldemodulators, such as computationally-implemented demodulators; analogdemodulator circuits; etc.), such as demodulators complementary to themodulators (e.g., configured to convert the encoded signal back into theoriginal sequence). However, the system 200 can additionally oralternatively include any other suitable optical detectors.

The beam director(s) 230 preferably functions to direct the opticalsignal(s) between aspects of the system 200 and the externalenvironment. For example, a beam director 230 can direct an emittedoptical signal (e.g., beam) from an optical emitter 210 to an externallocation 30 (within the external environment), wherein the opticalsignal reflects off the external location 30 (and/or other externallocations). The optical signal is preferably reflected back to the beamdirector 230, which directs the reflected signal to an optical detector220. However, the optical signal can additionally or alternatively bereflected to another beam director 230 (e.g., which directs the signalto the optical detector 220), to the optical detector 220, and/or to anyother suitable element(s) of the system 200. Each beam director 230 candirect one or more emitted signal and one or more reflected signals, andcan direct the signals between one or more optical emitters 210,external locations 30, and/or optical detectors 220 (e.g., as shown inFIG. 2B). In one example, the beam director 230 includes one or moremirrors, preferably moving and/or moveable mirrors such as rotatingmirrors (e.g., continuously rotating) and/or MEMS-based mirrors (e.g.,configured to move in response to control inputs), which can direct theoptical signal to many external locations 30 over time (e.g., scanningthe beam over the locations as the mirror rotates). However, the system200 can additionally or alternatively include any other suitable beamdirectors, or include no beam director.

The processing module(s) 240 preferably function to: control otherelements of the system 200, such as the optical emitters 210 (e.g.,controlling optical emission and/or modulation) and/or beam directors230 (e.g., controlling the direction of the beam); receive data fromother elements of the system 200, such as the optical detectors 220(e.g., receiving signals associated with light detection); and/orprocess (e.g., interpret) the received data, such as to determineinformation about the external environment (e.g., positions of theexternal locations 30). The processing module 240 is preferablycommunicatively (e.g. electronically) coupled to the optical emitters210, optical detectors 220, beam directors 230, and/or any othersuitable elements of the system. The processing module 240 preferablyincludes one or more processors (e.g., CPU, GPU, microprocessor, FPGA,ASIC, etc.) and/or storage units (e.g., Flash, RAM, etc.), but canadditionally or alternatively include any other suitable elements. Insome variations, the processing module 240 (and/or a supplementaryprocessing module) can be physically separated from the other elementsof the lidar system (e.g., wherein the lidar system includes acommunication module, such as a wireless communication module,configured to communicate with the processing module). For example, theprocessing module 240 can be a remote computing system (e.g.,Internet-connected server), and the lidar system can communicate withthe remote computing system (e.g., wherein some or all computations ofthe method are performed by the remote computing system). However, thesystem 200 can additionally or alternatively include any other suitableprocessing modules.

3. Method.

3.1 Determining a Signal.

Determining a signal S110 preferably functions to determine the signalthat the lidar system outputs, which can function to control variousaspects of object detection performance. Determining the signal S110preferably includes determining a sequence length S111, determining asequence S112, and/or encoding the sequence S113 (e.g., as shown in FIG.3A), and can additionally or alternatively include any other suitableelements.

Determining a sequence length S111 preferably functions to controltradeoffs between various system performance metrics (e.g., as describedbelow in further detail). The sequence length is preferably a bit-length(e.g., wherein the sequence is a binary sequence) but can additionallyor alternatively be any other suitable metric associated with sequencesize. The same sequence length is preferably used for multiplesequences, such as concurrently-emitted sequences (e.g., wherein aplurality of sequences are output substantially concurrently, such aseach output by a different optical emitter of the system; example shownin FIG. 3B) and/or serial sequences (e.g., a time series of multiplesequences, emitted by a single optical emitter of the system).Alternatively, different sequence lengths can be used for a singlecontinuous signal and/or multiple, concurrently-emitted signals.

The sequence length is preferably determined based on one or moredesired performance metrics (e.g., to achieve at least a minimumperformance level for a first set of metrics, to maximize performanceaccording to a second set of metrics, etc.). The sequence length can be:automatically determined (e.g., selected, calculated, etc.) based onoperating context, such as geographic location, system kinematics (e.g.,velocity, acceleration), presence of objects detected within a givenphysical range, performance metric values, and/or other contextualvariables; automatically determined based on a set of target performancemetric values (e.g., received from a user, determined based on operatingcontext); manually determined; and/or otherwise determined. For example,the method can include: receiving target values for one or moreperformance metrics, and selecting the sequence length associated withthe received performance metric target values (e.g., from a sequencelength-performance metric value table or other data structure). Theassociation between the performance metric value and the sequence lengthcan be: predetermined (e.g., calculated, tested), iterativelydetermined, and/or otherwise determined. In another example, the methodcan include: adjusting the sequence length until the performance metricssatisfy a set of performance metric target values. However, the sequencelength can be otherwise determined.

The performance metrics can include accuracy, range, resolution,latency, power consumption, and/or any other suitable metrics.

Accuracy can include detection failure probability (e.g., “completemiss”, such as described in more detail in the appendix), detecteddistance accuracy (e.g., “Cramer-Rao lower bound” or “CRLB”), and/or anyother suitable accuracy metrics. Accuracy is typically improved withlonger sequences. In some examples, the sequence length is selected sothat the CRLB is less than, no more than, and/or substantially equal toa threshold distance uncertainty, such as 0.1, 0.2, 0.5, 1, 2, 3, 4, 5,6, 7, 8, 9, 10, 15, 20, 30, 50, 100, 0.01-0.1, 0.1-1, 1-3, 3-7, 7-20,20-100, or 100-1000 cm. In a specific example, the threshold distanceuncertainty is 5 cm (e.g., the sequence length is selected to achieve aCRLB less than or equal to 5 cm).

Range is preferably the maximum distance at which an object can bereliably detected while implementing the method 200 (e.g., without thepossibility of an aliasing and/or range ambiguity issue, such as arisingfrom periodicity of the output signal; while maintaining the failureprobability below a threshold value, such as less than a 0.1%, 0.2%,0.5%, 1%, 2%, 5%, or 10% complete miss probability, preferably less thana 1% complete miss probability; while receiving sufficiently strongreturn signals to reliably perform the method; etc.). Because the signalperiod typically increases with sequence length (e.g., for a fixedsymbol rate, it increases linearly), range typically increases withlonger sequences (e.g., wherein, to avoid potential periodic rangeambiguity, the range is less than or equal to half the distance that thesignal propagates during one period of the signal, corresponding to theround-trip propagation time of the signal reflecting off a maximum-rangeobject). Additionally or alternatively, the effective range may belimited by the strength of the return signals received by the system(e.g., wherein return signals reflected from more distant objects in theenvironment may be weaker than those reflected from closer objects). Anincreased sequence length can increase the discrimination power of thematched filter and/or can increase the detection integration time, whichcan enable more reliable detection of more distant objects (and/or otherweakly-returning objects) in the environment. In some examples, thesequence length (and/or other signal parameters, such as symbol rate) isselected so that the range (e.g., ambiguity-limited range, return signalstrength-limited range, etc.) is more than, no less than, and/orsubstantially equal to a threshold distance, such as 50, 100, 150, 200,250, 275, 300, 325, 350, 400, 450, 500, 600, 10-50, 50-150, 150-450, or450-1000 m. In a first specific example, the threshold distance is 300m. In a second specific example, the threshold distance is 200 m,limited by return signal strength, which can correspond to a sequencelength that would enable an ambiguity-limited range of 1-5 km (e.g.,approximately 2 km).

Latency is preferably the amount of time per sweep (e.g., time betweenconsecutive signal outputs at a particular beam orientation, such ascorresponding to beam outputs at all the probed external locations).Latency typically becomes worse (larger) with longer sequences. Forexample, for a fixed resolution, an increased signal period (e.g.,which, for a fixed symbol rate, increases linearly with sequence length)corresponds to a dwell time at each beam orientation, and thus to anincrease latency.

Resolution is preferably the angular spacing between adjacent beamdirections (e.g., the angle defined between the vectors from the opticalemitter to each of two adjacent external locations). Resolutiontypically becomes poorer (e.g., larger spacing between points) withlonger sequences. For example, for a fixed latency, an increased signalperiod corresponds to fewer beam orientations per sweep (e.g., as thetime per sweep must be at least equal to the product of the number ofbeam orientations per sweep and the signal period).

In some embodiments, the sequence length is selected to be in the range10-10,000 bits (e.g., between 100 and 5000 bits). However, S111 canadditionally or alternatively include determining any other suitablesequence length(s) in any suitable manner.

Determining a sequence S112 preferably functions to determine one ormore unique sequences based on the sequence length (e.g., wherein eachsequence is of the length determined in S111). Each sequence ispreferably a digital sequence, such as a binary sequence, but thesequences can additionally or alternatively include any other suitablesequences.

The sequences are preferably determined to achieve a high degree oforthogonality (e.g., orthogonality between different sequences,orthogonality between encoded signals corresponding to the differentsequences, orthogonality to environmental noise, etc.). Accordingly, thesequences are preferably determined to meet the following criteria(and/or a subset of the criteria).

First, each sequence (and/or the corresponding encoded signal,preferably a periodically repeating signal) preferably has highauto-correlation at zero time delay (and, for the corresponding encodedsignal, preferably at time delays equal to integer multiples of theencoded signal period) and low (e.g., substantially zero; less than athreshold amount, such as relative to the zero time delayauto-correlation; etc.) auto-correlation away from zero time delay(e.g., more than a threshold time delay; for the corresponding encodedsignal, preferably excluding time delays equal to and/or close to, suchas within the threshold time of, integer multiples of the encoded signalperiod).

Second, each sequence (and/or the corresponding encoded signal,preferably a periodically repeating signal) preferably has low (e.g.,substantially zero; less than a threshold amount, preferably relative tothe zero time delay auto-correlation and/or to any other suitablereference value, such as less than 0.1%, 0.2%, 0.5%, 1%, 2%, 5%, 10%,20%, 30%, or 50% of the reference value; etc.) cross-correlation withother signals present in the system's environment (e.g., signals thatmay be detected by the detector; other signals that are output by thesystem, such as signals corresponding to other such sequences; constantand/or substantially-constant signals, such as from a steady state lightsource; etc.). This low cross-correlation can enable discriminationbetween the detected signals (e.g., following reflection of an outputsignal off an external location), such as by code-division multipleaccess (CDMA) techniques (e.g., asynchronous CDMA) and/or othertechniques.

In some embodiments, S112 includes determining multiple sequences (e.g.,each associated with a different emitter, such as different emitters ofthe system, of different systems, etc.), preferably each having the samesequence length (e.g., a single sequence length determined in S111). Insuch embodiments, the sequences are preferably determined to all satisfythe above criteria. In a first example, the sequences are selected froma set of Gold codes and/or other predetermined sequences with highorthogonality. In a specific example, the sequences are selected from aset of predetermined sequences for a given sequence length (e.g.,orthogonal sequences or Gold codes having a given sequence length),wherein the sequence length can be determined based on the targetperformance metrics. In this example, the system can maintain a databaseof orthogonal sequence sets for each of a plurality of sequence lengths.The database can optionally include a matched filter set for eachorthogonal sequence set (e.g., Fourier transforms and/or discreteFourier transforms of each of the sequences and/or corresponding encodedsignals). In a second example, the sequences are pseudorandom sequences(e.g., pseudorandom binary sequences), such as maximum length sequences.In a third example, the sequences are determined using one or moreoptimization techniques (e.g., stochastic optimization technique, suchas simulated annealing) based on one or more of the criteria(preferably, based on a cost function associated with all the criteria).In a specific example of the third example, iterations of theoptimization technique are applied until all sequences (and/or thecorresponding encoded signals) achieve a minimum threshold degree oforthogonality. However, the sequences can additionally or alternativelybe determined in any other suitable manner.

Encoding the sequence S113 preferably functions to generate an encodedsignal based on the sequence (e.g., for each sequence determined inS112, generating a corresponding encoded signal). The generated signalis preferably periodic, repeating the encoded sequence, more preferablywherein there is no (or substantially no) temporal gap between sequencerepeats (e.g., wherein the encoded sequence restarts as soon as theprevious iteration ends).

The sequence can be encoded using a modulation method (or multiplemethods), preferably a digital modulation method (e.g., onto a carriersignal such as a sinusoid). The modulation method is preferably aphase-shift keying (e.g., BPSK, QPSK, 8-PSK, higher order PSK, etc.),but can additionally or alternatively include quadrature amplitudemodulation (QAM), frequency-shift keying (FSK), amplitude-shift keying(ASK), and/or any other suitable modulation method. Alternatively, nocarrier signal and/or modulation method can be used (e.g., directlymapping bits and/or symbols to output intensities, such as mapping 0bits to a low or substantially zero intensity and mapping 1 bits to ahigh intensity; etc.).

Encoding the sequence S113 can optionally include determining anencoding frequency (e.g., symbol rate). For example, reducing theencoding frequency can reduce the computational load associated withelements of the method (e.g., S140 and/or S150), thereby reducing powerconsumption and/or enabling use of a less performant processing module(e.g., in systems that include or can include multiple differentprocessing modules; corresponding to a permanent reduction in encodingfrequency to enable use of less expensive and/or complex hardware;etc.). However, reducing the encoding frequency can also affect otherperformance metrics. For example, given a fixed sequence length, areduced encoding frequency will typically result in a worse CRLB,resolution, and/or latency (but may also result in an increased range,due to increased dwell time at each beam orientation). The same encodingfrequency is preferably used for all sequence encodings performed inS113, but alternatively different sequences can be encoded usingdifferent encoding frequencies. In a first example, determining theencoding frequency includes selecting one of two frequencies, such aseither a high-performance frequency (e.g., 50, 75, 100, 125, 150, 200,500, 1000, 50-200, 200-1000, or 1000-5000 MHz) or a low-power frequency(e.g., 5, 10, 20, 50, 75, 100, 1-10, 10-60, or 60-200 MHz). In a secondexample, determining the encoding frequency includes selecting afrequency in a range between the high-performance frequency and thelow-power frequency. Alternatively, a fixed encoding frequency (e.g.,10, 20, 50, 75, 100, 125, 150, 200, 500, 1000, 1-10, 10-60, 60-200,200-1000, or 1000-5000 MHz) can be used, such as a fixed 100 MHzfrequency, and/or the encoding frequency (or frequencies) can bedetermined in any other suitable manner.

However, S110 can additionally or alternatively include determining thesignal(s) in any other suitable manner.

3.2 Outputting the Signal.

Outputting the signal S120 preferably functions to emit an output (e.g.,a beam, preferably a beam of light) that includes the signal to beoutput (e.g., the signal determined in S110). S120 can includecontrolling a transducer, preferably an optical emitter such asdescribed above (e.g., a laser), to output the signal. For example, amodulator (e.g., as described above, such as regarding the system 200)can be employed to include the signal in the output. S120 preferablyincludes continuously outputting the signal (e.g., for a periodicsignal), but can alternatively include outputting the signal a singletime and/or any other suitable number of times with any suitable timing.In embodiments including multiple transducers (e.g., multiple opticalemitters, such as multiple lasers), S120 preferably includes emittingmultiple outputs, more preferably concurrently or substantiallyconcurrently (e.g., emitting all the outputs continuously orsubstantially continuously, emitting pulsed and/or sporadic outputs atsubstantially the same time as each other, etc.). However, the multipleoutputs can additionally or alternatively be emitted with any othersuitable timing.

During S120, the beam director is preferably controlled to direct theoutput signal toward one or more external locations 30 (e.g., asdescribed above, such as regarding the system 200). Upon reaching theexternal location(s), the beam can be reflected (e.g., back toward thesystem). In one example, the beam director can be controlled to directthe beam substantially in a first direction over a first dwell timeinterval (e.g., substantially equal to one period of the signal), thenin a second direction over a second dwell time interval, preferablysubstantially equal in duration to the first dwell time interval, and soon, eventually substantially returning to the first direction andrepeating continuously (e.g., until the output parameters, such assequence length, resolution, symbol rate, etc., are altered).

However, S120 can additionally or alternatively include outputting thesignal(s) in any other suitable manner.

3.3 Receiving a Return Signal.

Receiving a return signal S130 preferably functions to detect one ormore reflections of the output signal (e.g., from one or more objectswithin an environment surrounding the system, such as objects at theexternal location(s)). The signal can be received at a transducer (e.g.,of the system, such as close to and/or otherwise collocated with theoptical emitter or other output transducer of the system), preferably anoptical detector (e.g., photodiode, such as an avalanche photodiode(APD), etc.), such as described above regarding the system 200. In someembodiments (e.g., wherein multiple signals are output substantiallyconcurrently), multiple signals (e.g., reflections of different outputsignals, different reflections of a single output signal, etc.) can bereceived at the transducer during S130 (e.g., received substantiallyconcurrently and/or otherwise temporally overlapping). The return signalis preferably a reflection (e.g., direct reflection, specularreflection, etc.) of the output signal. However, S130 can additionallyor alternatively include receiving any return signal associated with(e.g., induced by) the output signal, and/or receiving any othersuitable signals.

The received signal(s) are preferably sampled (e.g., by a circuit, suchas an analog-to-digital converter circuit, that samples an electricaloutput of the transducer, such as the current and/or voltage generatedby the transducer in response to reception of the received signals) at asufficient rate to resolve the signal(s), such as sampling at a rate atleast twice the bandwidth of the anticipated signal(s). In one example,the received signals are sampled at a rate of at least 2.5 times thesymbol rate of the output signals (e.g., for a 100 MHz symbol rate,corresponding to a 125 MHz output signal bandwidth, sampling at a rateof at least 250 MHz).

However, the return signal can additionally or alternatively be receivedin any other suitable manner.

3.4 Analyzing the Return Signal.

Analyzing the return signal S140 preferably functions to determine theposition of one or more external locations (e.g., off of which thesignal was reflected) relative to the system. Analyzing the returnsignal S140 preferably includes selecting a sample from the returnsignal S141, filtering the sample S142, and/or determining informationbased on the signal S143 (e.g., as shown in FIG. 4A). However, analyzingthe return signal S140 can additionally or alternatively includedetermining additional information S144 and/or any other suitableelements.

Selecting a sample from the return signal S141 preferably functions toselect a portion of the return signal for analysis. The selected sampleis preferably a contiguous window of the received signal. The samplewindow is preferably sufficiently long in duration to capture an entireperiod of the output signal. In one example, the sample duration ispreferably no less than the sum of the signal period (e.g., equal to thesequence length divided by the symbol rate) and the maximum propagationdelay (e.g., equal to twice the range divided by the speed of signalpropagation, such as the speed of light in the environment surroundingthe system, which corresponds to the round-trip propagation time for anoutput signal that reflects off an external location at a distance equalto the range). However, S141 can additionally or alternatively includeselecting a window of any other suitable duration, and/or selecting anyother suitable sample.

Filtering the sample S142 preferably functions to isolate portions ofthe sample associated with (e.g., substantially matching) thecorresponding output signal. S142 preferably includes performing adigital filtering process (e.g., performed computationally), such asimplemented by a processing module (e.g., as described above). However,S142 can additionally or alternatively include otherwise performing thefiltering process (e.g., analog and/or digital filtering process, suchas one implemented by a filter circuit). The filter applied to thesample is preferably a matched filter (or substantially matched filter)for the corresponding output signal, but can additionally oralternatively be any other suitable filter.

In one embodiment, S142 includes determining a convolution (e.g.,circular convolution) of the output signal with the sample, preferablywherein one of the two are time-reversed (e.g., convolution of atime-reversed version of the periodic output signal with the sample, orconvolution of the periodic output signal with a time-reversed versionof the sample), such as a circular convolution of a time-reversedversion of the periodic output signal with the sample. For example,determining the convolution can include: determining a Fourier transform(e.g., discrete Fourier transform, such as the FFT) of the sample,determining a Fourier transform (e.g., discrete Fourier transform) ofthe output signal (and/or retrieving a previously-determined Fouriertransform of the output signal, such as one determined for a prioriteration of S142), multiplying the transformed output signal with thetransformed sample, and determining an inverse Fourier transform (e.g.,inverse discrete Fourier transform) of the product (which is theconvolution of the two).

S142 preferably generates a filtered sample that is a function of delaytime. The filtered sample is typically a discrete function (e.g., thesample and/or output signal includes data only at discrete points intime, the calculation is performed at discrete points in delay time,etc.) but can alternatively be a continuous function and/or any othersuitable function.

S142 can optionally include zero-padding the sample (e.g., wherein oneor more zero-valued points are inserted into the sample, such as betweeneach observed point of the sample determined in S130). The sample can bezero-padded before performing the filtering, and/or the filtered samplecan be zero-padded after filtering.

However, S142 can additionally or alternatively include filtering thesample in any other suitable manner.

Determining information based on the signal S143 preferably functions todetect the presence and/or absence of (and/or to determine information,such as distance, optical properties, etc., regarding) objects in theenvironment (e.g., the external locations off of which the output signalis reflected). S143 is preferably performed based on the filtered samplegenerated in S142, but can additionally or alternatively be performedusing the as-received sample selected in S141 and/or any other suitableinformation associated with the signal (e.g., received signal).

S143 can optionally include determining a noise floor of the sample. Thenoise floor can be determined based on the sample selected in S141,based on a calibration sample, preferably collected while the outputsignal is not being emitted (e.g., while no output signals are beingemitted, when all other output signals are being emitted, etc.), basedon any other suitable sample, estimated (e.g., based on typicalconditions), and/or determined in any other suitable manner. The noisefloor can be determined based on (e.g., equal to) a measure (e.g.,median, average, alpha-trimmed average, inter-quartile average, etc.) ofa power spectrum of the sample used to determine the noise floor (e.g.,the sample selected in S141, the calibration sample, etc.).

S143 preferably includes determining a delay time corresponding to anextremum of the data (e.g., a maximum of the sample, preferably thefiltered sample). This delay time is preferably determined using one ormore interpolation techniques (e.g., wherein the determined delay timecorresponds to the maximum-valued interpolated point). Suchinterpolation can have several benefits, including, for example,improving detection accuracy and/or enabling CRLB estimation.

For example, S143 can include determining an interpolated delay time(e.g., corresponding to an extremum of the interpolated data) byperforming a continuous curve interpolation (e.g., parabolicinterpolation, polynomial interpolation such as using a polynomial oforder 2, 3, 4, 5, 6, 7-10 or any other suitable order polynomial, sincfunction interpolation, Taylor-series interpolation, etc.), a discreteFourier transform-based interpolation (e.g., zero-padding a frequencyspectrum associated with a discrete Fourier transform of the data,convolving the zero-padded frequency spectrum with an interpolationkernel such as a sinc function kernel, and generating interpolated timedomain data by determining an inverse discrete Fourier transform of theconvolution), and/or any other suitable interpolation technique(s). Theinterpolation is preferably performed using only (or substantially only)linear computational operations, which can enable rapid computation, butcan additionally or alternatively be performed using any other suitableoperations. The delay time can additionally or alternatively bedetermined using one or more regression techniques (e.g., to determine acontinuous curve, such as a curve of one of the types described aboveregarding interpolation and/or any other suitable type of curve, thatfits the data or a subset thereof, such as a subset near the extremum).

S143 can optionally include applying a delay time correction (e.g.,after interpolation and/or regression). For example, the method caninclude correcting the interpolated delay time based on a correctionrelationship (e.g., predetermined relationship, such as determinedduring a system calibration, fixed for all such systems, etc.) betweenthe interpolated delay time and the corrected delay time, such as arelationship associated with an analytical curve (e.g., polynomial, suchas a polynomial of order 2, 3, 4, 5, 6, 7-10 or any other suitable orderpolynomial) and/or a numerical relationship (e.g., stored in a lookuptable).

In one example, the interpolated delay time is determined by performinga parabolic interpolation using three data points: the extremal datapoint and the point neighboring the extremal data point on either side.In a variation of this example, the interpolated delay time is thencorrected based on a polynomial correction relationship (e.g.,associated with a sixth-order polynomial of the interpolated delaytime).

However, S143 can alternatively include determining the delay timewithout interpolation (e.g., wherein the determined delay time is thetime corresponding to the maximum-valued discretized point of thesample), and/or determining the delay time in any other suitable manner.In embodiments in which a noise floor is determined, if the determineddelay time corresponds to a point exceeding the noise floor (e.g.,greater than the noise floor, a value proportional to the noise floor,greater by more than a threshold amount, etc.; considering a singlepoint, a peak including at least a threshold number of points, etc.),the delay time can be considered to represent a return (e.g., detectionevent), whereas points not exceeding the noise floor are preferably notconsidered to represent returns. If no noise floor is determined, anydelay time determined as described here is preferably considered torepresent a return.

This delay time (e.g., if considered to represent a return) correspondsto the propagation time of the output signal (e.g., time betweenemission from the optical emitter and reception at the opticaldetector). Thus, the delay time typically corresponds to the distance tothe external location from which the beam reflected (e.g., wherein thedelay time is equal to twice the distance divided by the signalpropagation speed, typically the speed of light).

The information determined in S143 (e.g., delay time and/or distancecorresponding to each return) is preferably stored in association withinformation associated with the detected object orientation with respectto the system (e.g., the beam direction). For example, the relativelocation of the object with respect to the system can be stored (e.g.,wherein many such returns result in the determination and/or storage ofa point cloud representing the environment surrounding the system), suchas stored as a point in 3-dimensional space (e.g., wherein the origin ofthe space represents the system). Optionally, other information can bestored in association with this information, such as the correspondingvalue (e.g., of the raw and/or interpolated sample), phase information,and/or any other suitable information.

However, S143 can additionally or alternatively include determining anyother suitable information in any suitable manner.

S140 can optionally include determining additional information S144. Insome embodiments, S144 can function to detect multiple extrema (e.g.,corresponding to multiple reflections) in a single sample. For example,S144 can enable recognition of “multi-return” events (e.g., wherein abeam is incident on the edge of an object, and thus a first portion ofthe beam is reflected by the object which a second portion of the beamcontinues on, possibly to be reflected by a second object; wherein abeam is incident on a semi-transparent object, and thus the beam ispartially reflected by the object and partially transmitted through theobject, possibly to be reflected by a second object; etc.). Preferably,S144 includes detecting all discernable extrema of interest (e.g.,maxima above the noise floor).

In one embodiment, S144 includes, after performing S143, altering thesample (e.g., filtered sample) to remove the peak that includes thedelay time determined in S143 (e.g., as shown in FIG. 5 ). In a firstexample, removing the peak includes selecting the peak by finding thenearest local minimum on each side of the determined delay time (whichcorresponds to the maximum), and altering all data between those minima(e.g., setting all values between the minima to zero, linearlyinterpolating between the minima, etc.). In a second example, removingthe peak includes performing a peak-fitting procedure to select the peak(e.g., determining a peak fit function corresponding to the peak), thensubtracting the peak fit values (e.g., values of the peak fit function)from the corresponding points of the sample. In a third example,removing the peak includes approximating a selection of the peak byselecting a window of points (e.g., predetermined number of points,predetermined delay time window, etc.) on each side of the determineddelay time (preferably including the point at the determined delaytime), and altering all data within the window (e.g., setting all valuesbetween the minima to zero, linearly interpolating between the pointsjust outside either side of the window, etc.). However, the peak canadditionally or alternatively be removed (and/or otherwise diminished,marked to be ignored, etc.) in any other suitable manner.

In this embodiment, after removing the peak, S143 is repeated using thealtered sample (e.g., wherein this repetition of S143 can determine asecond delay time, corresponding to the maximum value of the alteredsample). The process of removing peaks and then repeating S143 using thenewly-altered sample is preferably repeated until no additional returnsare found (e.g., all peaks that exceed the noise floor have beenremoved).

In a second embodiment, S144 includes performing a modified version ofS143 in which multiple extrema (e.g., in the filtered sample) and/orassociated delay times are determined substantially concurrently (e.g.,all determined during a single pass through the filtered sample). Inthis embodiment, S144 is preferably performed instead of S143, but canadditionally or alternatively be performed after S143 and/or with anyother suitable timing. In this embodiment, S144 preferably includessearching the filtered sample for local extrema (preferably maxima, butoptionally minima), wherein the first several or top (e.g., largest orsmallest magnitude) several extrema are stored. In an example of thisembodiment, a specific number of buffers are designated for storinginformation associated with the extrema (e.g., delay time, magnitude,etc.). Upon finding an extremum, the associated information is stored inan empty buffer. In a first variation, if no empty buffers remain, andthe search for extrema terminates (e.g., and S144 is complete). In asecond variation, if no empty buffers remain, the magnitude of thecurrent extremum is compared to the least significant (e.g., for maxima,smallest magnitude) stored extremum; if the current extremum is moresignificant, its associated data is stored in the buffer, replacing thepreviously-stored information associated with the less significantextremum.

However, S144 can additionally or alternatively include determining anyother suitable information in any suitable manner.

In embodiments in which multiple signals are output concurrently and/orclose in time (e.g., wherein several such signals may be receivedconcurrently in S130), S140 is preferably performed for each such outputsignal (e.g., as shown in FIG. 4B). For example (e.g., wherein thesequence length and symbol rate for all the signals is equal), a singlesample can be selected (as described above regarding S141) for all suchoutput signals, and then some or all remaining elements of S140 (e.g.,S142, S143, S144, etc.) can be performed (e.g., independently) for eachsuch output signal, using the same sample. Because the different outputsignals preferably have high mutual orthogonality (e.g., as describedabove), a high degree of discrimination between the different outputsignals can be enabled by this method (e.g., wherein most noiseassociated with the other output signals is filtered out in S142).Embodiments of the method can additionally or alternatively achieve highmutual interference immunity (e.g., immunity to interference from noiseoriginating from other sources, such as from other lidar systems and/orany other suitable emitters), especially for longer sequence lengths, asthese noise sources will also typically have reasonable highorthogonality to the output signals used by the lidar system.

However, S140 can additionally or alternatively include any othersuitable elements performed in any suitable manner.

3.5 Repeating Elements of the Method.

The method 100 can optionally include repeating one or more of theelements described above. One embodiment includes performing S120 and/orS130 (e.g., continuously performing S120 and S130, preferablysubstantially concurrently), preferably while repeating S140 and/orchanging the beam direction (e.g., sweeping the beam around theenvironment, such as described above). In this embodiment, all orsubstantially all of the signal received in S130 is preferably analyzedover the iterations of S140 (e.g., wherein for each iteration of S140, adifferent sample of the received signal, preferably the sampleimmediately following the previous sample, is used).

In a variation of this embodiment, some or all elements of Silo canoptionally be repeated (e.g., periodically, such as after a thresholdperiod of time, a threshold number of iterations of S140, a thresholdnumber of sweeps of the beam, etc.; sporadically; in response totriggers; etc.), wherein S120, S130, and/or S140 can continue to beperformed (e.g., based on the new sequence(s) determined in the mostrecent iteration of S110). In a first example of this variation, a newsequence length is selected (e.g., to alter some or all of theperformance metrics, such as accuracy, range, resolution, latency,etc.), such as described above regarding S111, after which S112 isperformed based on the new sequence length. In a second example, a newsequence (or sequences) is selected (e.g., as described above regardingS112) using the same sequence length as before. This second example canoptionally be performed if the sequence orthogonality (e.g., to externalnoise sources, such as noise from other lidar systems) is suspected tobe poor (e.g., if signal discrimination performance is poor). Forexample, if another nearby lidar system (e.g., mounted to a vehicleoperating near the present lidar system) is using one or more outputsignals similar to (e.g., not sufficiently orthogonal to) one or more ofthe current output signals of the present lidar system, the method maynot achieve sufficient immunity to this interference source. Thus, bychanging the sequence(s), greater mutual interference immunity may beachieved. This second example can additionally or alternatively beperformed periodically, sporadically, and/or with any other suitabletiming (e.g., changing operation to diagnose whether the system isoperating as desired), and/or performed for any other suitable reason.

However, the method 100 can additionally or alternatively includerepeating any other suitable elements with any suitable timing.

An alternative embodiment preferably implements the some or all of abovemethods in a computer-readable medium storing computer-readableinstructions. The instructions are preferably executed bycomputer-executable components preferably integrated with acommunication routing system. The communication routing system mayinclude a communication system, routing system and a pricing system. Thecomputer-readable medium may be stored on any suitable computer readablemedia such as RAMs, ROMs, flash memory, EEPROMs, optical devices (CD orDVD), hard drives, floppy drives, or any suitable device. Thecomputer-executable component is preferably a processor but theinstructions may alternatively or additionally be executed by anysuitable dedicated hardware device.

Although omitted for conciseness, embodiments of the system and/ormethod can include every combination and permutation of the varioussystem components and the various method processes, wherein one or moreinstances of the method and/or processes described herein can beperformed asynchronously (e.g., sequentially), concurrently (e.g., inparallel), or in any other suitable order by and/or using one or moreinstances of the systems, elements, and/or entities described herein.

The FIGURES illustrate the architecture, functionality and operation ofpossible implementations of systems, methods and computer programproducts according to preferred embodiments, example configurations, andvariations thereof. In this regard, each block in the flowchart or blockdiagrams may represent a module, segment, step, or portion of code,which comprises one or more executable instructions for implementing thespecified logical function(s). It should also be noted that, in somealternative implementations, the functions noted in the block can occurout of the order noted in the FIGURES. For example, two blocks shown insuccession may, in fact, be executed substantially concurrently, or theblocks may sometimes be executed in the reverse order, depending uponthe functionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts, or combinations of special purpose hardware andcomputer instructions.

As a person skilled in the art will recognize from the previous detaileddescription and from the figures and claims, modifications and changescan be made to the preferred embodiments of the invention withoutdeparting from the scope of this invention defined in the followingclaims.

We claim:
 1. A method for environment mapping, comprising: generating asubstantially continuous laser output representative of a periodicoutput signal that encodes a code sequence; throughout a time period,continuously transmitting the substantially continuous laser output intoan environment; during the time period, at an optical sensor, receivinga return signal comprising a reflection, from an object within theenvironment, of the substantially continuous laser output; determining asample indicative of a contiguous time window of the return signal,wherein a duration of the contiguous time window is greater than aperiod of the periodic output signal; generating a filtered sample,comprising filtering the sample based on the code sequence; based on thefiltered sample: determining an extremum of the filtered sample; anddetermining a delay time associated with the extremum; and based on thedelay time, determining a relative location of the object.
 2. The methodof claim 1, wherein filtering the sample based on the code sequencecomprises applying, to the sample, a matched filter for the periodicoutput signal.
 3. The method of claim 2, wherein applying the matchedfilter comprises determining at least one of: a circular convolution ofthe sample with a time-reversed version of the periodic output signal;or a circular convolution of the periodic output signal with atime-reversed version of the sample.
 4. The method of claim 1, whereindetermining the delay time comprises: determining an interpolatedsub-sample comprising the extremum; and determining the delay time basedon the interpolated sub-sample.
 5. The method of claim 4, whereindetermining the interpolated sub-sample comprises performing acontinuous curve interpolation.
 6. The method of claim 1, wherein thereturn signal further comprises a second reflection, from a secondobject within the environment, of the substantially continuous laseroutput, the method further comprising: based on the filtered sample,determining a second delay time associated with the second object; andbased on the second delay time, determining a relative location of thesecond object.
 7. The method of claim 6, further comprising, beforedetermining the second delay time, determining a first peak regionassociated with the extremum; wherein determining the second delay timecomprises: determining a second extremum of the filtered sample, whereinthe second extremum is not within the first peak region, wherein amagnitude of the extremum is greater than a magnitude of the secondextremum; and determining the second delay time based on the secondextremum.
 8. The method of claim 1, further comprising: at the opticalsensor, after receiving the return signal, receiving a second returnsignal comprising a second reflection, from a second object within theenvironment, of the substantially continuous laser output; determining asecond sample indicative of a second contiguous time window of thesecond return signal; generating a second filtered sample, comprisingfiltering the second sample based on the code sequence; based on thesecond filtered sample, determining a second delay time associated witha second extremum of the filtered sample; and based on the second delaytime, determining a relative location of the second object.
 9. Themethod of claim 1, further comprising: generating a second substantiallycontinuous laser output encoding a second periodic output signal;throughout the time period, continuously transmitting the secondsubstantially continuous laser output into the environment; generating asecond filtered sample, comprising filtering the sample based on thesecond code sequence, wherein the return signal further comprises asecond reflection, from a second object within the environment, of thesecond substantially continuous laser output; based on the secondfiltered sample: determining a second extremum of the second filteredsample; and determining a second delay time associated with the secondextremum; and based on the second delay time, determining a relativelocation of the second object.
 10. The method of claim 1, whereingenerating the substantially continuous laser output comprisesmodulating a substantially continuous-wave carrier signal based on acode sequence encoded using a phase-shift keying.
 11. The method ofclaim 1, further comprising, before generating the substantiallycontinuous laser output, determining the code sequence such that across-correlation between the periodic output signal and other opticalsignals received at the optical sensor is less than a threshold value.12. The method of claim 11, further comprising, before determining thecode sequence: selecting a candidate code sequence; generating acandidate laser output representative of a candidate output signal thatencodes the candidate code sequence; transmitting the candidate laseroutput; at the optical sensor, receiving a test signal; and based on thetest signal, determining that a test cross-correlation between thecandidate output signal and the other optical signals is greater thanthe threshold value; wherein the code sequence is determined in responseto determining that the test cross-correlation is greater than thethreshold value.
 13. The method of claim 1, further comprising: beforethe time period: based on a first set of desired performance metrics,determining a first sequence length, wherein the first set of desiredperformance metrics comprises at least one of: accuracy, range,resolution, and latency; and determining the code sequence based on thefirst sequence length, wherein a length of the code sequence is equal tothe first sequence length; based on the return signal, determining asecond sequence length; determining a second code sequence based on thesecond sequence length, wherein a length of the second code sequence isequal to the second sequence length; generating a second substantiallycontinuous laser output representative of a second periodic outputsignal that encodes the second code sequence; throughout a second timeperiod following the time period, continuously transmitting the secondsubstantially continuous laser output into the environment; during thesecond time period, at the optical sensor, receiving a second returnsignal comprising a second reflection, from the object, of the secondsubstantially continuous laser output; determining a second sampleindicative of a second contiguous time window of the second returnsignal; generating a second filtered sample, comprising filtering thesecond sample based on the second code sequence; based on the secondfiltered sample: determining a second extremum of the second filteredsample; and determining a second delay time associated with the secondextremum; and based on the second delay time, determining an updatedrelative location of the object.
 14. A method for environment mapping,comprising: generating a first substantially continuous optical outputrepresentative of a first periodic output signal; generating a secondsubstantially continuous optical output representative of a secondperiodic output signal; throughout a time period, continuouslytransmitting the first and second substantially continuous opticaloutputs into an environment; during the time period, at an opticalsensor, receiving a return signal, the return signal comprising: a firstreflection, from a first object within the environment, of the firstsubstantially continuous optical output; and a second reflection, from asecond object within the environment, of the second substantiallycontinuous optical output; determining a sample by selecting acontiguous time window of the return signal; generating a first filteredsample, comprising filtering the sample based on the first codesequence; determining a first delay time associated with the firstfiltered sample; based on the first delay time, determining a relativelocation of the first object; generating a second filtered sample,comprising filtering the sample based on the second code sequence;determining a second delay time associated with the second filteredsample; and based on the second delay time, determining a relativelocation of the second object.
 15. The method of claim 14, furthercomprising, before the time period, determining the first and secondcode sequences such that a cross-correlation between the first andsecond periodic output signals is substantially zero.
 16. The method ofclaim 15, further comprising, before the time period, determining asequence length, wherein the lengths of the first and second codesequences are each equal to the sequence length.
 17. The method of claim14, further comprising, before the time period, determining a set ofcode sequences, each code sequence of the set associated with arespective periodic output signal that encodes the code sequence,wherein: determining the set of code sequences comprises performing astochastic optimization such that, for each pair of code sequences ofthe set, a respective cross-correlation between the respective periodicoutput sequences associated with the code sequences of the pair is lessthan a threshold value; and the set of code sequences comprises thefirst and second code sequences.
 18. The method of claim 14, wherein:the first periodic optical output is transmitted into the environment bya first laser; and the second periodic optical output is transmittedinto the environment by a second laser.
 19. The method of claim 14,wherein the optical sensor comprises a photodiode, wherein the returnsignal is received at the photodiode.
 20. The method of claim 19,wherein the first and second reflections are received at the photodiodeconcurrently.
 21. The method of claim 1, wherein the code sequencecomprises a binary sequence of 0 bits and 1 bits, wherein generating thesubstantially continuous laser output comprises generating a highintensity output for each 1 bit and generating a substantially zerointensity output for each 0 bit.